Ambiguous expressions often appear in physical and mathematical texts. It is common practice to omit multiplication signs in mathematical expressions. Also, it is common to give the same name to a variable and a function, for example,
f
=
f
(
x
)
{\displaystyle f=f(x)}
. Then, if one sees
f
=
f
(
y
+
1
)
{\displaystyle f=f(y+1)}
, there is no way to distinguish whether it means
f
=
f
(
x
)
{\displaystyle f=f(x)}
multiplied
by
(
y
+
1
)
{\displaystyle (y+1)}
, or function
f
{\displaystyle f}
evaluated
at argument equal to
(
y
+
1
)
{\displaystyle (y+1)}
. In each case of use of such notations, the reader is supposed to be able to perform the deduction and reveal the true meaning.

Therefore, for most practical purposes decision-makers are unlikely to need to rank pairs defined on more than two criteria, thereby reducing the burden on decision-makers. For example, approximately 95 explicit pairwise rankings are required for the value model referred to above with eight criteria and four categories each (and 2,047,516,416 undominated pairs to be ranked); 25 pairwise rankings for a model with five criteria and three categories each; and so on.
[1]
The real-world applications of PAPRIKA referred to earlier suggest that decision-makers are able to rank comfortably more than 50 and up to at least 100 pairs, and relatively quickly, and that this is sufficient for most applications.

The ZAPROS method (from Russian for ‘Closed Procedure Near References Situations’) was also proposed;
[71]
however, with respect to pairwise ranking all undominated pairs defined on two criteria “it is not efficient to try to obtain
full
information”.
[72]
As explained in the present article, the PAPRIKA method overcomes this efficiency problem.

The PAPRIKA method can be easily demonstrated via the simple example of determining the point values (weights) on the criteria for a value model with just three criteria – denoted by ‘a’, ‘b’ and ‘c’ – and two categories within each criterion – ‘1’ and ‘2’, where 2 is the higher ranked category.
[1]

This value model’s six point values (two for each criterion) can be represented by the variables a1, a2, b1, b2, c1, c2 (a2 > a1, b2 > b1, c2 > c1), and the eight possible alternatives (2
3
= 8) as ordered triples of the categories on the criteria (abc): 222, 221, 212, 122, 211, 121, 112, 111. These eight alternatives and their total score equations – derived by simply adding up the variables corresponding to the point values (which are as yet unknown: to be determined by the method being demonstrated here) – are listed in Table 2.

Undominated pairs are represented as ‘221
vs
(versus) 212’ or, in terms of the total score equations, as ‘a2 + b2 + c1
vs
a2 + b1 + c2’, etc. [Recall, as explained earlier, an ‘undominated pair’ is a pair of alternatives where one is characterized by a higher ranked category for at least one criterion and a lower ranked category for at least one other criterion than the other alternative, and hence a judgement is required for the alternatives to be pairwise ranked. Conversely, the alternatives in a ‘dominated pair’ (e.g. 121
vs
111 – corresponding to a1 + b2 + c1
vs
a1 + b1 + c1) are inherently pairwise ranked due to one having a higher category for at least one criterion and none lower for the other criteria (and no matter what the point values are, given a2 > a1, b2 > b1 and c2 > c1, the pairwise ranking will always be the same).]